Particle analysis and sorting apparatus and methods

ABSTRACT

A particle analyzer, comprising a source of a beam of pulsed optical energy; a detector comprising a number of spectral detection channels to detect optical signals resulting from interactions between the beam and particles in a sample (such as, e.g., fluorescence signals), and to convert the optical signals into respective electrical signals; optical paths from the source to the sample and from the sample to the detector; a flowcell connected with the optical paths and with a flow path for a suspension of particles; a signal processing module capable of: receiving the electrical signals from the detector; mathematically combining individual decay curves in the signals into a decay supercurve; allocating individual components of the supercurve to discrete bins of predetermined time constants; and quantifying the relative contribution of individual components to the supercurve; a particle sorting actuator; an actuator driver; and at least one particle collection receptacle.

INTRODUCTION

The invention pertains to the fields of Particle Analysis and ParticleSorting. In particular, embodiments of the invention are capable ofincreased multiplexing in Flow Cytometry and Cell Sorting.

BACKGROUND

Cellular analysis and sorting have reached a high level ofsophistication, enabling their widespread use in life science researchand medical diagnostics alike. Yet for all their remarkable success astechnologies, much remains to be done in order to meet significant needsin terms of applications.

One area of continuing unmet need is that of multiplexing. Multiplexingrefers to the practice of labeling cells, beads, or other particles withmultiple types of biochemical or biophysical “tags” simultaneously anddetecting those tags uniquely, so as to generate a richer set ofinformation with each analysis. The most commonly used tags inmicroscopy and flow cytometry are fluorescent molecules, orfluorophores. A fluorophore may be a naturally occurring fluorophore; itmay be an added reagent; it may be a fluorescent protein [like, e.g.,Green Fluorescence Protein (GFP)] expressed by genetic manipulation; itmay be a byproduct of chemical or biochemical reactions, etc.Fluorophores may be used as they are, relying on their native affinityfor certain subcellular structures such as, e.g., DNA or RNA; or theymay be linked to the highly specific biochemical entities known asantibodies, in a process referred to as conjugation. As a particularantibody binds to a matching antigen, often on the surface of a cell,the fluorophore conjugated to that antibody becomes a “tag” for thatcell. The presence or absence of the fluorophore (and therefore of theantigen the fluorophore-conjugated antibody is intended to specificallybind to) can then be established by excitation of the cells in thesample by optical means and the detection (if present) of thefluorescence emission from the fluorophore. Fluorescence emission into acertain range of the optical spectrum, or band, is sometimes referred toin the art as a “color;” the ability to perform multiplexed analysis istherefore sometimes ranked by the number of simultaneous colorsavailable for detection.

The use of multiple distinct tags (and detection of their associatedcolors) simultaneously allows the characterization of each cell to amuch greater degree of detail than possible with the use of a singletag. In immunology particularly, cells are classified based on theirexpression of surface antigens. The identification of a large number ofdifferent surface antigens on various types of cells has motivated thecreation of a rich taxonomy of cell types. To uniquely identify theexact type of cell under analysis, it is therefore often necessary toperform cell analysis protocols involving simultaneously a large numberof distinct antibody-conjugated tags, each specifically designed toidentify the presence of a particular type of antigen on the cellsurface.

In flow cytometry of the prior art, methods have been devised tosimultaneously label cells with up to twenty or more differentfluorescent tags and detect their respective colors. Commerciallyavailable instrumentation is generally limited to simultaneous detectionof fifteen colors or less, and most commonly less than about ten colors.One of the main challenges of routinely performing highly multiplexedanalysis (as the practice of simultaneously detecting more than about adozen separate colors is sometimes called) is the technical difficultyof keeping detection of each color (and its associated tag) separatefrom detection of all the other ones. FIG. 1 illustrates one key aspectof the challenge of multiplexed measurement of fluorescence in the priorart. The graph in this FIG. 1 depicts various fluorescence emissioncurves (thin solid lines) of intensity (I) as a function of wavelength(λ), all curves having been normalized to their respective peakintensities. In applications of fluorescence detection, it is verycommonly desirable to employ several different colors, or spectralbands, of the electromagnetic spectrum, and to assign each band to adifferent fluorophore. Different fluorophores can be selected, on thebasis of their average emission spectra, so as to obtain relativelydense coverage of a certain range of the electromagnetic spectrum, andthereby maximize the amount of information that can be extracted in thecourse of a single experiment or analysis “run.” However, when strivingto maximize spectral coverage, one of the common undesirableconsequences is spectral overlap. The shaded portions in FIG. 1illustrate the problem caused by spectral overlap between adjacentfluorescence spectra. In this particular illustrative example, fivespectral fluorescence “bands” or colors (the five emission curvespeaking at different wavelengths) span a certain desired range of theelectromagnetic spectrum, such as, e.g., the visible portion of thespectrum from about 400 nm to about 750 nm in wavelength. The shadedportions indicate sections of the spectrum where it is impossible, usingspectral means alone, to decide whether the signal comes from one or theother of the two bands adjacent to the overlapping region; accordingly,the portions of the spectrum corresponding to significant overlap arecommonly discarded, resulting in inefficient use of the spectrum.Additionally, even after discarding such portions, residual overlapremains in the other portions, resulting in contamination of one bandfrom signals from other bands. Attempts at negating the deleteriouseffects of such contamination go under the heading of “compensation.”This spectral overlap problem is variously described in the literatureand the community as the “crosstalk,” the “spillover,” the “compensationproblem,” etc., and it is a major factor in limiting the maximum numberof concurrent spectral bands, or colors, that can be employed in afluorescence detection experiment.

It would be desirable, then, to provide a way to perform highlymultiplexed analyses of particles or cells with a reduced or eliminatedimpact of spectral crosstalk.

In cell analysis of the prior art, methods have also been devised tosimultaneously label cells with up to thirty of more different tags anddetect their respective characteristics. For example, the techniqueknown in the art as mass cytometry employs not fluorescence as a way todistinguish different tags, but mass spectrometry, where the tagsincorporate not fluorophores, but different isotopes of rare earthsidentifiable by their mass spectra. One major drawback of this approachis that the protocol of analysis is destructive to the sample, the cellsand their tags becoming elementally vaporized in the process ofgenerating the mass spectra. This approach is therefore not suited tothe selection and sorting of cells or other particles following theiridentification by analysis.

It would be further desirable, then, to provide a way to performselection and sorting of particles or cells based on nondestructivehighly multiplexed analysis with a reduced or eliminated impact ofspectral crosstalk.

SUMMARY

An apparatus for analyzing an optical signal decay, comprising:

-   -   a source of a beam of pulsed optical energy;    -   a sample holder configured to expose a sample to said beam;    -   a detector, the detector comprising a number of spectral        detection channels, said channels being sensitive to distinct        wavelength sections of the electromagnetic spectrum and being        configured to detect optical signals resulting from interactions        between said beam and said sample, said channels being further        configured to convert said optical signals into respective        electrical signals;    -   a first optical path from said source of said beam to said        sample;    -   a second optical path from said sample to said detector; and    -   a signal processing module, capable of:    -   receiving said electrical signals from said detector;    -   mathematically combining individual decay curves in said        electrical signals into a decay supercurve, said supercurve        comprising a number of components, each component having a time        constant and a relative contribution to said supercurve;    -   extracting time constants from said supercurve; and    -   quantifying the relative contribution of individual components        to said supercurve.

An apparatus for analyzing an optical signal decay, comprising:

-   -   a source of a beam of pulsed optical energy, wherein said source        of said beam of pulsed optical energy is an internally modulated        laser;    -   a flowcell configured as an optical excitation chamber for        exposing to said beam a sample comprising a suspension of        particles and for generating optical signals from interactions        between said beam and said particles;    -   a detector, the detector comprising a number of spectral        detection channels, said channels being sensitive to distinct        wavelength sections of the electromagnetic spectrum and being        configured to detect said optical signals, said channels being        further configured to convert said optical signals into        respective electrical signals, wherein said optical signals        comprise a fluorescence signal;    -   a first optical path from said source of said beam to said        sample, said first optical path being connected with said        flowcell;    -   a second optical path from said sample to said detector, said        second optical path being connected with said flowcell;    -   a signal processing module, wherein said signal processing        module comprises one of an FPGA, a DSP chip, an ASIC, a CPU, a        microprocessor, a microcontroller, a single-board computer, a        standalone computer, and a cloud-based processor, said signal        processing module being further capable of:    -   receiving said electrical signals from said detector;    -   mathematically combining individual decay curves in said        electrical signals into a decay supercurve, said supercurve        comprising a number of components, each component having a time        constant and a relative contribution to said supercurve;    -   extracting time constants from said supercurve; and    -   quantifying the relative contribution of individual components        to said supercurve;    -   a flow cytometer;    -   a flow path for said suspension of particles, said flow path        being connected with said flowcell;    -   a particle sorting actuator connected with said flow path,        wherein said particle sorting actuator is based on at least one        flow diversion in said flow path, and wherein said particle        sorting actuator is further based on one of a transient bubble,        a pressurizable chamber, a pressurizable/depressurizable chamber        pair, and a pressure transducer;    -   an actuator driver connected with said actuator, said driver        being configured to receive actuation signals from said signal        processing module; and    -   at least one particle collection receptacle connected with said        flow path.

An apparatus for analyzing an optical signal decay, comprising:

-   -   a source of a beam of pulsed optical energy;    -   a sample holder configured to expose a sample to said beam;    -   a detector, the detector comprising a number of spectral        detection channels, said channels being sensitive to distinct        wavelength sections of the electromagnetic spectrum and being        configured to detect optical signals resulting from interactions        between said beam and said sample, said channels being further        configured to convert said optical signals into respective        electrical signals;    -   a first optical path from said source of said beam to said        sample;    -   a second optical path from said sample to said detector; and    -   a signal processing module, capable of:    -   receiving said electrical signals from said detector;    -   mathematically combining individual decay curves in said        electrical signals into a decay supercurve, said supercurve        comprising a number of components, each component having a time        constant and a relative contribution to said supercurve;    -   allocating individual components of said supercurve to discrete        bins of predetermined time constants; and    -   quantifying the relative contribution of individual components        to said supercurve.

An apparatus for analyzing an optical signal decay, comprising:

-   -   a source of a beam of pulsed optical energy, wherein said source        of said beam of pulsed optical energy is an internally modulated        laser;    -   a flowcell configured as an optical excitation chamber for        exposing to said beam a sample comprising a suspension of        particles and for generating optical signals from interactions        between said beam and said particles;    -   a detector, the detector comprising a number of spectral        detection channels, said channels being sensitive to distinct        wavelength sections of the electromagnetic spectrum and being        configured to detect said optical signals, said channels being        further configured to convert said optical signals into        respective electrical signals, wherein said optical signals        comprise a fluorescence signal;    -   a first optical path from said source of said beam to said        sample, said first optical path being connected with said        flowcell;    -   a second optical path from said sample to said detector, said        second optical path being connected with said flowcell;    -   a signal processing module, wherein said signal processing        module comprises one of an FPGA, a DSP chip, an ASIC, a CPU, a        microprocessor, a microcontroller, a single-board computer, a        standalone computer, and a cloud-based processor, said signal        processing module being further capable of:    -   receiving said electrical signals from said detector;    -   mathematically combining individual decay curves in said        electrical signals into a decay supercurve, said supercurve        comprising a number of components, each component having a time        constant and a relative contribution to said supercurve;    -   allocating individual components of said supercurve to discrete        bins of predetermined time constants; and    -   quantifying the relative contribution of individual components        to said supercurve;    -   a flow cytometer;    -   a flow path for said suspension of particles, said flow path        being connected with said flowcell;    -   a particle sorting actuator connected with said flow path,        wherein said particle sorting actuator is based on at least one        flow diversion in said flow path, and wherein said particle        sorting actuator is further based on one of a transient bubble,        a pressurizable chamber, a pressurizable/depressurizable chamber        pair, and a pressure transducer;    -   an actuator driver connected with said actuator, said driver        being configured to receive actuation signals from said signal        processing module; and    -   at least one particle collection receptacle connected with said        flow path.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a wavelength diagram illustrating the spectral overlap(spillover) in multiplexing approaches of the prior art.

FIG. 2 is a time-domain diagram illustrating a frequency-based approachto measuring single-exponential fluorescence lifetime of the prior art.

FIG. 3 is a time-domain diagram illustrating a time-correlatedsingle-photon counting approach to measuring fluorescence lifetime ofthe prior art.

FIG. 4(a) is a linear-linear time-domain diagram and FIG. 4(b) is alog-linear time-domain diagram illustrating a single-exponential decaycurve resulting from pulsed excitation; FIG. 4(c) is a linear-lineartime-domain diagram and FIG. 4(d) is a log-linear time-domain diagramillustrating a double-exponential decay curve resulting from pulsedexcitation.

FIG. 5 is a wavelength-lifetime diagram coupled with a wavelengthdiagram illustrating a multiplexing approach dense in both spectralbands and lifetime bins in accordance with one embodiment.

FIG. 6 is a wavelength-lifetime diagram coupled with a wavelengthdiagram illustrating a multiplexing approach sparse in both spectralbands and lifetime bins in accordance with one embodiment.

FIG. 7 is a schematic illustration of a system configuration of anapparatus for analysis of single particles in a sample in accordancewith one embodiment.

FIG. 8 is a schematic illustration of a system configuration of anapparatus for analysis and sorting of single particles in a sample inaccordance with one embodiment.

FIG. 9 is a schematic representation of the light collection anddetection subsystem of a particle analyzer/sorter with a single spectraldetection band in accordance with one embodiment.

FIG. 10 is a schematic representation of the light collection anddetection subsystem of a particle analyzer/sorter with multiple spectraldetection bands in accordance with one embodiment.

FIG. 11 is a time-domain diagram illustrating a signal processingsequence in accordance with one embodiment: (a) interaction envelope dueby a flowing particle crossing the beam; (b) excitation pulses; (c)effective excitation pulses; (d) fluorescence emission pulses with decaycurves; (e) segmentation of individual pulse signals; (f) constructionof a supercurve.

FIG. 12(a) is a log-linear time-domain diagram illustrating atriple-exponential decay supercurve constructed from individual pulsesignals resulting from pulsed excitation; FIG. 12(b) is a log-lineartime-domain diagram illustrating the process of computing successiveindex-pair differences, determining supercurve knee points, anddetermining supercurve time-constant branches.

FIGS. 13(a) and (b) are schematic plan-view illustrations of two steps,or states, of a particle analysis/sorting method that uses a sortingactuator in accordance with one embodiment.

FIGS. 14(a) and (b) are schematic cross-sectional illustrations of twosteps, or states, of a particle analysis/sorting method with two sortingstates and one-sided actuation in accordance with one embodiment.

FIGS. 15(a) and (b) are schematic cross-sectional illustrations of twosteps, or states, of a particle analysis/sorting method with two sortingstates and one-sided actuation in accordance with one embodiment.

FIGS. 16(a) and (b) are schematic cross-sectional illustrations of twosteps, or states, of a particle analysis/sorting method with two sortingstates and two-sided actuation in accordance with one embodiment.

FIGS. 17(a)-(d) are schematic cross-sectional illustrations of fourstates of a particle analysis/sorting method with five sorting statesand one-sided actuation that uses multiple sorting channels inaccordance with one embodiment.

FIG. 18(a) is a flow chart describing a sequence of principal operationsinvolved in the performance of a method of lifetime analysis inaccordance with one embodiment.

FIG. 18(b) is a flow chart describing a sequence of principal operationsinvolved in the performance of a method of particle analysis inaccordance with one embodiment.

FIG. 18(c) is a flow chart describing a sequence of principal operationsinvolved in the performance of a method of highly multiplexed particleanalysis in accordance with one embodiment.

FIG. 19 is a schematic representation of a data processing system toprovide an analyzer/sorter in accordance with one embodiment.

DETAILED DESCRIPTION

One possible solution to the spectral overlap problem in highlymultiplexed particle and cell analysis would be to utilize, besidespectral information, another type of information with which to index orencode the tags used to label cell characteristics. By adding anindependent quantity that can be detected and measured, one cansignificantly increase the number of combinations available to label andidentify cell types. There would follow then a reduced need to fit alarge number of independent spectral bands into a limited region of theelectromagnetic spectrum, since the total number of availablecombinations could be allocated based on two independent quantitiesinstead of just one.

It is one objective of the present invention to provide fluorescencelifetime as that independent quantity, to be combined with spectrallabeling to generate a highly multiplexed set of independentcombinations with which to uniquely tag different cell characteristicsor cell types with a reduced or eliminated impact of spectral crosstalk.

It is a further objective of the present invention to provide thecombination of fluorescence lifetime and spectral fluorescence labelingto aid not only in the highly multiplexed analysis of cells or otherparticles, but also in the selection and sorting of cells or otherparticles with a reduced or eliminated impact of spectral crosstalk.

Fluorescence lifetime is an aspect of the fluorescence emission processgoverned by quantum-mechanical laws. Fluorescence is the absorption byan atom or molecule of a packet of optical energy (a photon) of acertain wavelength and the subsequent emission by the same atom ormolecule of a packet of optical energy (another photon) at a longerwavelength. The amount of time elapsed between absorption and emissionvaries stochastically, but given an ensemble of isolated identical atomsor molecules, the frequency distribution of such elapsed times of theentire ensemble follows an exponential decay curve. The time constant ofsuch a curve (the 1/e time) is referred to as the lifetime for thatfluorescence transition for that atom or molecule.

Different molecular entities display different fluorescence transitions,characterized by different optimal wavelengths of optical absorption,different peak wavelengths of optical emission, and differentfluorescence lifetimes. Certain molecular entities display fluorescencetransitions with similar spectral characteristics (the profiles ofemission as a function of wavelength schematically illustrated inFIG. 1) but with different fluorescence lifetimes. And other molecularentities display fluorescence transitions with different spectralcharacteristics but with similar fluorescence lifetimes. Accordingly,molecular entities may be selected based on spectral characteristics(spectral emission profile) and fluorescence lifetime as essentiallyindependent quantities.

In order to use fluorescence lifetime as a multiplexing parameter inparticle analysis, one needs to provide the means to measure it. FIG. 2describes one aspect of measurements of fluorescence lifetime as carriedout in one approach in the prior art. The graph in this FIG. 2 depictstwo curves of optical intensity (I) as a function of time (t). In thisapproach, the intensity of optical excitation (thick solid line) ismodulated at a certain frequency, and the resulting fluorescence signal(thin dashed line) is analyzed. The effect of a finite fluorescencelifetime manifests itself primarily in the phase shift between themodulated excitation and the modulated emission curves. The maindrawback of this approach (so-called “phase-sensitive” or“frequency-domain” fluorescence lifetime) is that it can only probe onefluorescence lifetime component at a time, and is poorly suited toanalysis of samples where more than one lifetime component should bemeasured simultaneously. It is an objective of the current invention toovercome this limitation.

FIG. 3 illustrates the principle behind another approach to measurementof fluorescence lifetime in the prior art. This approach has beenreferred to in the literature as Time-Correlated Single-Photon Counting(TCSPC), and has been used particularly in fluorescence lifetime imagingapplications (FLIM). The graph depicted in this FIG. 3 shows two curvesof intensity (I) as a function of time (t), both normalized to unit peakintensity, and a histogram with associated bins. The first curve (thicksolid line) represents any one of many identical excitation pulses usedto interrogate a portion of the sample; the second curve (thin dashedline) represents the inferred fluorescence emission response from theportion of the sample under interrogation. This second curve is notmeasured directly, but is instead inferred by a numerical fit to ahistogram. A typical hypothetical histogram is shown as a series ofboxes superimposed upon the second curve. This histogram represents thefrequency distribution of arrival times of single fluorescence emissionphotons following excitation by a pulse. By exciting the same portion ofthe sample many times, a histogram is collected that faithfully reflectsthe underlying fluorescence decay curve. The main drawback of thisapproach is the very principle it is based on: single-photon counting.The method only works if a single photon is, on average, emitted as aresult of excitation. For typical decay curves, it is not uncommon torequire between tens of thousands and millions of repeated excitationsin order to acquire enough statistics in the histogram for acceptableaccuracy of results. Even at high pulse repetition rates, this approachnecessarily results in dwell times (the time spent acquiring data on asingle portion of the sample) on the order of milliseconds to seconds.Accordingly, TCSPC is an approach that has been successfully applied tostationary samples, but which is poorly suited to samples that arerapidly varying, unstable, flowing, or generally needing to be analyzedrapidly. It is an objective of the current invention to overcome thislimitation.

FIGS. 4(a)-(d) illustrate the importance of direct time-domainmeasurements of fluorescence lifetime. In each of FIGS. 4(a)-(d), agraph depicts the evolution in time (t) of the intensity (I) of twocurves: the optical excitation pulse (shown as thick solid lines 410,430, 450, and 470, in the four graphs, respectively) and the opticalemission curve (shown as thin dashed lines 425, 445, 465, and 485, inthe four graphs, respectively), both being normalized to unit peakintensity. In FIGS. 4(a) and 4(c), each of the two curves in each graph420 and 460 are plotted on a linear-linear scale; in FIGS. 4(b) and4(d), each of the two curves in each graph 440 and 480 are plotted on alog-linear scale (also known as a “semilog” scale). The graphs 420 and440 in FIGS. 4(a) and 4(b) illustrate the same curves, just plotted ondifferent scales; likewise, the graphs 460 and 480 in FIGS. 4(c) and4(d) illustrate the same curves, just plotted on different scales. Influorescence processes, a molecule (which can be naturally occurring,such as certain dyes; or manmade, such as the majority of fluorophoresin current use) exhibits a propensity for absorption of optical energywithin a certain range of wavelengths (referred to as its absorptionspectrum), followed by emission of optical energy into a different rangeof wavelengths (referred to as its emission spectrum). The process ofabsorption and emission in fluorescence is governed by quantum mechanicsand is influenced by several factors. Some of those factors areintrinsic to the molecule; other factors are environmental factors.Emission of a fluorescent photon occurs stochastically; given a largeenough collection of identical molecules (an ensemble), the collectiveemission of the ensemble will appear to decay over time. For ahomogeneous ensemble [depicted in FIGS. 4(a) and 4(b)], the cumulativecurve of fluorescence emission can be represented by a single decaylifetime (shown schematically as τ_(a) 421 in this case). In the semilogplot 440 of FIG. 4(b), the single-decay nature of the dashed emissioncurve 445 is evidenced by the presence of a single straight slope(indicated by its corresponding lifetime τ_(a) 441, corresponding to thesame τ_(a) as 421 in plot 420). For a heterogeneous ensemble [depictedin FIGS. 4(c) and 4(d)] consisting of two distinct populations, thecumulative curve of fluorescence emission can be better represented by acompound function comprising two different decay lifetimes (shownschematically as τ_(b) 461 and τ_(c) 462 in this case). In the semilogplot 480 of FIG. 4(d), the double-decay nature of the dashed emissioncurve 485 is evidenced by the presence of two straight-sloped branches(indicated by their respective lifetimes τ_(b) 481 and τ_(c) 482,respectively corresponding to τ_(b) 461 and τ_(c). 462 in plot 460)joined at a “knee.” The shape of the decay curve gives informationregarding the environment of the molecules in the ensemble. Assumingthat the ensemble in FIGS. 4(c) and 4(d) consisted of a single kind ofmolecular entity, the appearance of two distinct lifetimes would suggestthat molecules in the ensemble are exposed to two differentenvironmental influences, one of them causing a significant alterationto the native fluorescence lifetime of the molecules. Without a directrecording in real time of the actual shape of the emission decay curveof the ensemble of fluorescence molecules, the distinction between thecases depicted in FIGS. 4(a)-(b) and FIGS. 4(c)-(d) would be lost, andwith it the information regarding the environment of the molecularspecies. The analysis made possible by this direct time-domain approachcan be variously referred to as multi-component or multi-exponentialfluorescence decay analysis.

A practical example of application of the principle of analysis ofmulti-exponential, or multi-component, fluorescence decay is found inthe analysis of cells. A eukaryotic cell consists primarily of amembrane, a cytoplasm, a nucleus, and various subcellular cytoplasmicstructures. The biochemical microenvironment experienced by a moleculewithin a cell is greatly affected by factors such as the localconcentration of electrolytes, local pH, local temperature, etc. When afluorophore enters a cell, its microenvironment may be very different,depending on whether the fluorophore is freely floating in thecytoplasm, binds to a molecule (e.g., RNA) or to an enzyme or othersubcellular structures within the cytoplasm, or crosses the nuclearmembrane to bind to, e.g., DNA in the nucleus. When exposed to opticalexcitation, the sub-ensemble of fluorophores bound to DNA in the nucleusmay exhibit a very different lifetime from, e.g., the sub-ensemble offluorophores freely floating in the cytoplasm. By analyzing the compounddecay curve of the entire ensemble, one must be able to distinguishbetween the two (or more) different contributions to the lifetime, as anaverage single lifetime will blur the desired information and present anincomplete picture of the situation.

If the cell to be analyzed is stationary (as, e.g., adhered to asubstrate, or grown on a substrate, suitable for placement under amicroscope), existing microscopy tools could be used to spatiallyresolve physical locations within the cell, perform, e.g., highlyrepetitious experiments on single pixels (or voxels) spanning very smallportions of the cell, and repeat these measurements over all pixels (orvoxels) comprising the cell. There are however, many instances when thatapproach is not desirable, and it would be instead advantageous for thecell to be analyzed to be moving swiftly past the point ofinterrogation. One instance is when it is desirable to complete a set ofmeasurements on a cell or on a group of cells in a very short time, asis generally the case in clinical diagnostic applications, wheretime-to-results is a critical parameter on which may depend patients'health or lives. A related instance, also of great relevance in clinicaldiagnostics and drug discovery and development, but increasingly alsorecognized as important in basic scientific research, is when it isdesirable to complete a certain set of measurements on a very largecollection of cells in a practical amount of time, so as to generatestatistically relevant results not skewed by the impact of individualoutliers. Another instance is when it is desirable to performmeasurements on a cell in an environment that mimics to the greatestdegree possible the environment of the cell in its native physiologicalstate: As an example, for cells naturally suspended in flowing liquids,such as all blood cells, adhesion to a substrate is a very unnaturalstate that grossly interferes with their native configuration. There areyet instances where the details of the physical location within the cell(details afforded, at a price of both time and money, by high-resolutionmicroscopy) are simply not important, but where a proxy for specificlocations within the cell would suffice, given prior knowledge (based onprior offline studies or results from the literature) about thecorrelation between specific cell locations and values of the proxymeasurement.

There are also instances where, regardless of the speed at which ameasurement is carried out, and therefore regardless of whether themeasurement is performed on a flow cytometer, under a microscope, orunder some other yet experimental conditions, it would be desirable toreduce or eliminate the spectral crossover problem. Many analyticalprotocols in cell biology research, drug discovery, immunology research,and clinical diagnostics are predicated on the concurrent use ofmultiple fluorophores, in order to elucidate various properties ofhighly heterogeneous samples consisting of diverse cell populations,sometimes with uncertain origin or lineage. The spectral crossoverinherent in such concurrent use of available fluorophores presentlylimits the multiplexing abilities of tools in current use—be they cellsorters, cell analyzers, image-based confocal scanning microscopes, orother platform. Various schemes have been developed to quantify andmitigate the deleterious impact of spectral crossover, and are generallyreferred to as compensation correction schemes. These schemes, however,suffer from overcomplexity, lack of reproducibility, and difficulty inthe proper training of operators. It would be therefore advantageous toprovide various analytical platforms with a way to multiplex complexmeasurements without the same attendant spectral crossover issue as iscurrently experienced.

There are yet instances of cellular analysis where it is desirable toperform fluorescence lifetime measurements on molecular species nativeto the systems under study. In this case the process of fluorescence issometime referred to as autofluorescence or endogenous fluorescence, andit does not depend on the introduction of external fluorophores, butrather relies on the intrinsic fluorescence of molecules already present(generally naturally so) in the cell to be analyzed. Endogenousfluorescence is similar to the fluorescence of externally introducedfluorophores, in being subject to similar effects, such as the influenceof the molecular microenvironment on fluorescence lifetime. Accordingly,it would be advantageous to be able to resolve different states ofendogenous fluorescence on an analytical platform, so as to provide forsimple and direct differentiation between cells belonging to differentpopulations known to correlate with different values of endogenousfluorescence lifetime of one or more natively present compounds. Oneexample of practical application of the principle of endogenousfluorescence is in the differential identification of cancer cells fromnormal cells based on metabolic information.

FIG. 5 schematically illustrates a principle of the present invention,namely the ability to improve the multiplexing capacity of an analyticalinstrument by using fluorescence lifetime information. At the bottom ofFIG. 5 is a graph 550 depicting various fluorescence emission curves561-565 (thin solid lines) of intensity (I) as a function of wavelength(λ), all curves having been normalized to their respective unit peakintensity. In contrast to the prior art, where distinction betweendifferent fluorophores as cell labels or “markers” is performedexclusively by spectral means (the horizontal wavelength axis λ in graph550), in the present invention a separate, orthogonal dimension ofanalysis is added: the vertical lifetime τ axis in the graph 500 at top.Each fluorescence emission curve is represented by a “band”, shown inthe figure as a shaded vertical strip 511-515: FL₁ (511), FL₂ (512), FL₃(513), FL₄ (514), FL₅ (515), . . . . Similarly, different fluorescencelifetime values are represented by different values of τ, groupedtogether in “bins”, shown in the figure as shaded horizontal strips521-525: τ₁ (521), τ₂ (522), τ₃ (523), τ₄ (524), τ₅ (525), . . . . Eachof the bins is intended to schematically represent a relatively similargroup of lifetimes: the variation among the various lifetime values inthe τ₁ bin will generally be smaller than the difference between theaverage lifetimes of the τ₁ and τ₂ bins, the variation among the variouslifetime values in the τ₂ bin will generally be smaller than thedifference between the average lifetimes of the τ₁ and τ₂ bins and willalso generally be smaller than the difference between the averagelifetimes of the τ₂ and τ₃ bins, and so on.

FIG. 5 makes it plain that the wavelength axis and its associated bandsnow represent only one dimension of a virtual plane. The second, addeddimension of this virtual plane is represented by the fluorescencelifetime axis τ and its associated bins in graph 500. The schematicintersections of the wavelength bands and the lifetime bins are shown ingraph 500 as darker shaded regions 530 (of which only a few are labeled)in the λ-τ plane. The increased multiplexing of the present invention isexemplified by the fact that, for every one of the spectral (wavelength)bands generally available to current analytical platforms, the presentinvention offers several possible multiplexed lifetimes: As an example,the fluorescence band FL₂ (512) supports multiple fluorescence lifetimebins τ₁ (521), τ₂ (522), τ³ (523), τ₄ (524), τ₅ (525), . . . . For asystem with n distinct fluorescence bands and m distinct lifetime bins,the total theoretical number of independent combinations is n×m; to usea practical example, for a system with 6 distinct fluorescence bands and4 distinct lifetime bins, there are 6×4=24 mutually independentmultiplexed combinations available.

FIG. 5 also describes how a specific example of a multiplexedcombination would be resolved in the present invention. From thewavelength axis a particular spectral band (say, FL₃ band 513) isselected for analysis. This particular spectral band in practice wouldbe selected by spectral optical means, such as one or more of thin-filmfilters, dichroic beam splitters, colored glass filters, diffractiongratings, and holographic gratings, or any other spectrally dispersingmeans suitable for the task and designed to pass this band ofwavelengths preferentially over all others. The resulting optical signalcould still comprise any of a number of fluorescence lifetimes,depending on the instrument design and on the nature of the sample. Thespectral optical signal filtered through as FL₃ is detected, convertedto electronic form, and sent to an electronic signal processing unit fordigitization and further elaboration; see FIG. 10. The signal processingunit (further described below in reference to FIGS. 7 and 19) performsan analysis of the decay characteristics of the optical signalscorresponding to the particle under study, and allocates the variouscontributions to the overall signal from each possible band of lifetimevalues. A virtual electronic “bin” corresponding to the specific bin τ₄(524) of lifetimes would receive a value corresponding to the fractionof the signal that could be ascribed as resulting from a lifetime decaywithin the acceptable range relevant for the τ₄ band. The combination ofthe spectral filtering for FL₃ performed optically on the emitted signaland the lifetime filtering for τ₄ performed digitally on theelectronically converted optical signal results in narrowing downanalysis to a single multiplexing element: the shaded intersection 540marked with a thick solid square in graph 500 of FIG. 5.

The specific choice of FL₃ and τ₄ is only illustrative, in the sensethat any of the intersections between detectable spectral fluorescencebands and resolvable lifetime bins are potentially simultaneouslyaccessible by analysis—resulting in the increased multiplexing abilitydescribed above as desirable. FIG. 5 shows explicitly a set of allowablemultiplexed intersections for a prophetic example comprising 5 distinctfluorescence bands and 5 distinct lifetime bins: a resulting set of upto 5×5=25 separate, mutually independent combinations. This example isillustrative only: the number of possible combinations is not limited to25, being given instead by the number of individually separablefluorescence spectral bands multiplied by the number of individuallyseparable lifetime values bins. The theoretical maximum number ofindividually separable lifetime bins is related to the samplingfrequency of digitization, the repetition rate of excitation pulses, andthe duration (width) of each excitation pulse. In the limit ofexcitation pulses much shorter than lifetimes of interest (which aretypically in the tens of picoseconds to tens of nanoseconds, and whichin some cases reach microsecond levels or greater), the maximum numberof separable lifetime bins is given by the pulse repetition perioddivided by twice the digitization sampling period. Electronic, optical,and other noise effects in actual systems may significantly reduce thistheoretical maximum.

In practice it may be desirable to implement less than the theoreticalmaximum number of multiplexed combinations available. Some of thepractical reasons that may factor into the criteria for such a choice(which may be hard coded during design, or may alternately be left up tothe instrument operator) may include: the desire to reduce thecomputational complexity required for a full implementation of thepossible combinations; the desire to reduce the computational timerequired to perform a statistically acceptable analysis on the number ofpossible combinations; the desire to manufacture or to obtain a simpler,smaller, less costly instrument than would be needed for a fullimplementation of the theoretical maximum number of possiblecombinations; the desire for an operator to be able to operate theanalytical platform with a minimum of specialized training; and thedesire for a robust instrument designed to perform a reduced set ofoperations in a highly optimized fashion. Whichever the motivation, onemay choose to produce a “sparse” multiplexed configuration, where someof the possible multiplexing choices have been removed.

In one embodiment of the present invention, such sparseness isintroduced in the lifetime domain: Only a few of the possible lifetimebins are provided, the rest being removed and being replaced by gapsbetween the provided lifetime bins [e.g., removing bins τ₂ (522) and τ₄(524) in FIG. 5]. The advantage of this configuration over a denselypopulated lifetime configuration is that the relative sparseness of thelifetime bins simplifies the process of digitally distinguishing thelifetime contributions of the remaining bins to the optical emissionsignal.

In another embodiment of the present invention, the sparseness ofmultiplexing is introduced in the spectral domain: Only a few of thepossible wavelength bands are provided, the rest being removed and beingreplaced by gaps between the provided spectral bands [e.g., removingbands FL₂ (512) and FL₄ (514) in FIG. 5]. The advantage of thisconfiguration over a densely populated spectral configuration is thatthe relative sparseness of the spectral bands simplifies the handling ofany residual spectral overlap.

FIG. 6 shows an illustrative example (graph 600) of yet anotherembodiment of the present invention, where the sparseness ofmultiplexing has been introduced in both the spectral (graph 650 atbottom) and the lifetime domains simultaneously: Only a few of thepossible wavelength bands have been provided, the rest having beenremoved and being indicated in the figure by the gaps between theprovided spectral bands [e.g., between bands FL₁ (611) and FL₃ (613) andbetween bands FL₃ (613) and FL₅ (615)]; and only a few of the possiblelifetime bins have been provided, the rest having been removed and beingindicated in the figure by the gaps between the provided lifetime bins[e.g., between bins τ₁ (621) and τ₃ (623) and between bins τ₃ (623) andτ₅ (625)]. The resulting configuration, while having considerably fewerintersection points than the theoretical maximum, is however advantagedover a densely populated spectral and lifetime configuration by thereduction in the number of hardware components, the reduction in thecomplexity of the signal processing algorithms, by the relative increasein robustness and accuracy of the signal processing results, and by therelative simplicity of a training protocol for operation of theassociated instrument platform.

FIG. 7 illustrates schematically a system configuration of an exemplaryembodiment of the present invention, which provides an apparatus forhighly multiplexed particle analysis in a sample. In another embodiment,it provides an apparatus for lifetime analysis of particles in a sample.One or more light source 750, e.g., a laser, produces one or moreoptical energy (light) beams 722 with desired wavelength, power,dimensions, and cross-sectional characteristics. One or more modulationdrivers 752 provide modulation signal(s) 702 for the one or morerespective light sources, resulting in the beam(s) 722 becoming pulsed.The modulation drivers may optionally be internal to the lightsource(s). The pulsed beam(s) are directed to a set of relay optics 754(which can include, for instance, lenses, mirrors, prisms, or opticalfibers), which may additionally optionally perform a beam-shapingfunction. Here relay optics will be intended to represent means totransmit one or more beams from one point in the system to another, andwill also be intended to represent means to shape one or more beams interms of dimensions and convergence, divergence or collimation. Theoutput pulsed beam(s) 732 from the beam-shaping relay optics aredirected to another optional set of relay optics 758 (which can include,for instance, lenses, mirrors, prisms, or optical fibers), which mayadditionally optionally perform a focusing function. The beam-shapingoptics, the focusing optics, or both, may alternatively be incorporatedinto the light source module. The combined effect of the two sets ofrelay optics (the beam-shaping and the focusing sets) upon the inputbeam(s) from the light source(s) is to impart upon the beam(s) thedesired output beam propagation characteristics suitable forinterrogating particles. The second set of relay optics then directs thepulsed beam(s) 708 to the flowcell 700. The flowcell 700 provides forthe passage of particles to be analyzed (which can include, forinstance, cells, bacteria, exosomes, liposomes, microvesicles,microparticles, nanoparticles, and natural or synthetic microspheres) byconveying a sample stream 740 containing said particles as a suspension,and a stream of sheath fluid 742 that surrounds and confines said samplestream, as further described herein. An input portion of the flowcellfocuses, e.g., by hydrodynamic means, the sample stream and thesurrounding sheath stream to result in a tight sample core streamflowing through a microchannel portion of the flowcell, surrounded bysheath fluid. The tight sample core stream flowing past theinterrogation region of the flowcell typically exposes, on average, lessthan one particle at a time to the beam or beams for interrogation (thisis sometimes referred to in the art as “single-file” particleinterrogation). The sheath fluid and the sample core stream are directedto a single outlet 744 (and generally discarded as waste) after passagethrough the interrogation portion of the flowcell. As the interrogatingpulsed beam(s) of optical energy (light) interact with particles in thesample core stream by scattering, absorption, fluorescence, and othermeans, optical signals 710 are generated. These optical signals arecollected by relay optics in box 760 (which can include, for instance,single lenses, doublet lenses, multi-lens elements, mirrors, prisms,optical fibers, or waveguides) positioned around the flowcell, thenconveyed to filtering optics in box 760 (which can include, forinstance, colored filters, dichroic filters, dichroic beamsplitters,bandpass filters, longpass filters, shortpass filters, multibandfilters, diffraction gratings, prisms, or holographic optical elements)and then conveyed as filtered light signals 712 by further relay opticsin box 760 to one or more detectors 770 (which can include, forinstance, photodiodes, avalanche photodiodes, photomultiplier tubes,silicon photomultipliers, or avalanche photodiode microcell arrays). Thedetectors convert the optical signals 712 into electronic signals 772,which are optionally further amplified and groomed to reduce the impactof unwanted noise. The electronic signals are sent to an electronicsignal processing unit 790 [which generally comprises a digitizationfront end with an analog-to-digital converter for each signal stream, aswell as discrete analog and digital filter units, and may comprise oneor more of a Field-Programmable Gate Array (FPGA) chip or module; aDigital Signal Processing (DSP) chip or module; an Application-SpecificIntegrated Circuit (ASIC) chip or module; a single-core or multi-coreCentral Processing Unit (CPU); a microprocessor; a microcontroller; astandalone computer; and a remote processor located on a “digitalcloud”-based server and accessed through data network or wired orcellular telephony means], which executes further processing steps uponthe electronic signals. The processed signals 774 are then sent to adata storage unit 792 (which can include, for instance, a read-onlymemory unit, a flash memory unit, a hard-disk drive, an optical storageunit, an external storage unit, or a remote or virtual storage unitconnected to the instrument by means of a wired data ortelecommunication network, a Wi-Fi link, an infrared communication link,or a cellular telephony network link). The stored or preliminarilyprocessed data, or both, can also be made available to an operator foroptional inspection of results.

FIG. 8 illustrates schematically a system configuration of an exemplaryembodiment of the present invention, which provides an apparatus forhighly multiplexed analysis and sorting of particles in a sample. Inanother embodiment, it provides an apparatus for lifetime analysis andsorting of particles in a sample. It is similar in configuration to thesystem configuration of FIG. 7, except in that it additionally providesfor the capability to sort and collect particles based on theircharacteristics. The signal processing unit 890 generates in real timesorting control signals 876 based on the presence or absence or degreeor nature of predetermined characteristics of the particles to beanalyzed. For example, it may be desirable to identify and sortparticles that, upon excitation by the interrogating pulsed lightbeam(s), emit fluorescence in a predefined spectral band at a levelabove a predefined threshold. As another example, it may be desirable toidentify and sort particles that, upon excitation by the interrogatingpulsed beam(s), exhibit fluorescence decay curve with a lifetimecomponent in a certain range of values and at a percentage above apredefined threshold. Different criteria may be used in isolation orcombined in compound logical forms (such as AND, OR, NOT, as well asmore complex forms involving numerical comparisons of differentquantities, such as “greater than,” “less than,” and so forth). Theprocessing unit 890, once the processed signals from a given particlemeet the predefined set of sorting criteria, triggers a signal 876conveyed to an actuator driver 894. The actuator driver is an electroniccontrol module connected to one or more sorting actuators 880. Thesorting actuators may be positioned in, on, next to, or near theflowcell in the vicinity of, and downstream from, the interrogationregion. One or more of the sorting actuators 880 is temporarilyactivated by drive signal 878 from the actuator driver 894 in responseto the triggering signal 876 from the processing unit 890, resulting ina temporary diversion of the sample core stream, or of a portion of thesample core stream, away from the default sorting channel 846 and intoone or more sorting channels 848. The default sorting channel 846optionally directs the fluids it receives into a default receptacle 847.The sorting channel(s) 848 direct the sample core stream, in turn, torespective receiving sorting receptacle(s) 849. Once the temporaryactivation of one or more of the sorting actuators 880 is complete, theactuator(s) return to their resting state, and the sample core streamreturns to its default sorting channel 846. The sorting actuator(s) 880are controllable to achieve multiple actuation states, for instance,with an actuator driver 894, with a built-in control, with directvoltage or current control from the processing unit 890, or withelectrical signals coming directly from logic circuitry connected withthe one or more detectors 870.

In FIGS. 9 and 10, the relative orientation of fluid flow, lightpropagation, and transverse directions is shown, respectively, as theset of axes x, z, and y. The process steps involved in the performanceof some embodiments of the present invention are described here inreference to FIGS. 9 and 10, and are also further summarized inflow-chart fashion in FIG. 18(a).

FIG. 9 illustrates a cross-section, perpendicular to the direction offluid flow, of a possible light collection configuration of the presentinvention. A flowcell 900, of which the inner part is schematicallyindicated in the figure, provides a channel for fluid flow. Sheath fluid920 is provided to confine the fluid 930 carrying particles 955 to beanalyzed. The sheath fluid and the sample-carrying fluid are focusedinto the flowcell lumen, optionally by hydrodynamic means; such focusingproduces a tight sample core stream bounded by the sheath fluid. Aninterrogating light beam or beams 940 are provided to interact with theparticles in the sample core stream. The beam or beams, usually having aGaussian intensity profile, are generally focused into a relativelytight spot in the plane of the sample core stream. Particles to beanalyzed in the sample core stream interact with light in the beam orbeams 940 to generate optical signals 910 by optical processesincluding, for instance, scattering, absorption, or fluorescence. Theoptical signals 910 are collected by collection optics 960. Thecollected optical signals 912 are then conveyed (relayed) to spectralfiltering optics 962 to select appropriate spectral bands of the opticalsignals for detection. The spectral filtering optics 962 may be, forinstance, reflective, transmissive, absorptive, diffractive, orholographic in nature or based on interference, or a combinationthereof. The resulting spectrally filtered optical signals 914 are thenconveyed (relayed) as signals 916 by focusing optics 964 to a detector970. The detector converts the light signals 916 into electrical signals972, which are then conveyed to a processing unit 990 for furtheranalysis, processing, and optionally storage, as described above inreference to FIGS. 7 and 8 and as further discussed below. Together, thecollection optics 960 and the focusing optics 964 may be referred to asrelay optics.

In some embodiments, more than one spectral band output may begenerated. For instance, FIG. 10 illustrates a cross-section,perpendicular to the direction of fluid flow, of another possible lightcollection configuration of the present invention. It is similar inconcept to the configuration illustrated in FIG. 9 except that thespectral filtering optics 1062 produce more than one spectral bandoutput 1014 (A and B), separated according to spectral characteristics.Each spectral band is then conveyed (relayed) to a separate set offocusing optics 1064 (A and B) and separate detectors 1070 (A and B),resulting in respectively separate electrically converted signals 1072(A and B). The resulting electrical signals are then routed to signalprocessing unit 1090 for further elaboration. FIG. 10 depicts, for thesake of clarity, two sets of spectral bands, focusing optics, anddetectors; it will be apparent to those skilled in the art that anarbitrary number of such sets is encompassed by the scope of theinvention.

The process steps described below in conjunction with FIGS. 11(a)-(f),12(a) and 12(b) are also summarized in a flow-chart fashion in FIG.18(c).

FIG. 11 illustrates, for the specific case of implementation of thepresent invention on a flow cytometry platform, the principles involvedin excitation, emission, detection, and analysis of fluorescencelifetime signals from particles under analysis. The various panels ofthe figure will be referred to in the text that follows to betterillustrate the various steps of the signal transduction process. In eachpanel (a)-(f), a graph depicts the evolution over time (t) of certainoptical intensities (I). In every case except where noted, the opticalintensities are each normalized to unit peak values.

The graph 1110 in FIG. 11(a) depicts the canonical behavior of theoptical signals resulting from the interaction between an always-onexcitation light source (also referred to in the art as a constant-wave,or cw, source) and a particle passing through the region ofinterrogation (typically in a flow cell or other component having asimilar function). As the particle enters, then exits, the region ofinterrogation, the excitation interaction signal (the dash-dotted line1115) rises then falls, in concert with the spatial profile of the lightbeam used for interrogation, as measured along the line of passage ofthe particle. The particle, in this canonical pedagogical illustration,is assumed small in comparison with the dimension of the light beamalong the direction of passage of the particle; modifications to thisframework that generalize this to the case of particles of arbitrarysize are possible but are not informative for the purpose at hand, andare not taken up here. A typical light beam having dimensions, along theline of passage of particles to be analyzed, from less than 10 to morethan 100 microns, and a typical flow cytometer causing particles to passthrough the region of interrogation at flow velocities of below 0.1 tomore than 10 m/s, the range of possible durations of the excitationinteraction envelopes, as the shape of curve 1115 in FIG. 11(a) issometimes referred to, is quite wide, stretching from less than 1 us tomore than 1 ms. However, in most cases in current practice thefull-width at half-maximum (FWHM) of the excitation interaction envelopeis around a few microseconds.

The graph 1120 in FIG. 11(b) juxtaposes, for illustrative purposes, thecanonical interaction envelope 1115 from FIG. 11(a) (the dash-dottedline) with one possible configuration of excitation pulses from amodulated source of optical energy. The pulses are shown in a train ofuniformly repeated, essentially identical units (the sharp features 1122in thick solid lines); each pulse is short as compared to the FWHM ofthe canonical interaction envelope, and each pulse is separated fromneighboring pulses by a time generally larger than the width of thepulses themselves. One key aspect of the invention captured in thispanel 11(b) is that the modulation of the optical energy source (orsources) should result in a series of essentially identical pulses, eachshort compared to the typical interaction time, and each well separatedfrom the next.

The graph 1130 in FIG. 11(c) depicts the prophetic result of deliveringthe train of excitation pulses 1125 illustrated in FIG. 11(b) to aparticle flowing in a flow cell according to design and operatingparameters typical of flow cytometer constructions known in the art. Theresulting excitation interactions are shown as a series of pulses ofvarying height (features 1132 in thick solid lines) conforming to anoverall envelope (the dash-dotted line), said envelope corresponding tothe interaction envelope that would result, were the light beamcontinuous instead of pulsed and all other things remaining equal. Whilethe details of the interaction sequence would, generally, vary fromparticle to particle [for example, the detailed timewise location of theindividual interaction pulses 1132 in FIG. 11(c) under the overallenvelope is a function of the relative timing of the pulse train withrespect to the arrival of the particle], the general nature of theexcitation interaction as consisting of a series of pulses modulated bya “carrier” envelope is determined by the design and operatingparameters of the apparatus. In this graph 1130 of FIG. 11(c) theindividual interaction pulses are not normalized to unit intensity.

The graph 1140 in FIG. 11(d) adds another key element of the currentinvention to the picture, namely the ability to measure the temporalevolution of the fluorescence decay curves. The overall carrier envelope(dash-dotted line) and the individual excitation interaction pulses(features in thick solid lines) are as illustrated in FIG. 11(c). Thefluorescence decay curves are shown as thin dashed lines 1147. Eachfluorescence decay curve follows directly the optical excitationassociated with the interaction pulse immediately preceding it. It canbe appreciated that the fluorescence decay curves are, generally,asymmetric: While the rising portion is dominated by the absorption ofoptical energy from the excitation source, the waning portion (thedecay) is driven by the quantum mechanical processes of fluorescenceemission, which vary from molecule to molecule and are additionallyaffected by the molecular microenvironment, and generally result in acurve with a longer decay-side tail. In this graph 1140 of FIG. 11(d)the individual interaction pulses and the individual fluorescence decaycurves are not normalized to unit intensity.

It is a fundamental property of linear functions that the shape of acurve is unaffected by an arbitrary constant scaling factors: forexample, a Gaussian bell curve will remain a Gaussian bell curve nomatter what fixed multiplicative scaling factor may be applied to it. Acorollary of this is that if two curves are generated by the samefunction, an appropriate choice of a scaling factor can be found which,applied to one curve, turns it into the other one. Since the samelifetime processes are at work in each of the decay curves of graph11(d), they can be normalized to unit peak intensity. This optionalnormalization step does not affect the nature of the decay (i.e., itleaves the decay time constant, or lifetime, unaffected) while bringingall of the curves on the same scale for ease of comparison. In somecases, depending on the nature and degree of noise present on thesignal, the normalization step is omitted to achieve the best results;the rest of the process is illustrated here with this normalization stepomitted.

The next process step in the lifetime analysis algorithm involvessegmenting the signal sequence into individual decay curves. The dashedcurves 1147 in graph 1140 of FIG. 11(d) represent optical emissionsignals, such as, e.g., fluorescence decay curves; these optical signalsare detected by one or more detectors, converted into electrical signal,and digitized for further processing. In graph 1150 of FIG. 11(e) thesequence of pulse signals (dashed curves, representing digitizedelectrical signals corresponding to the optical signals they areconverted from) is broken mathematically into individual pulse signalsegments 1151-1156 (A, B, C, . . . ) while maintaining a consistentphase across the entire sequence; that is, a selected feature of eachpulse (e.g., the peak, the midpoint of its rising edge, etc.) is chosenas the reference, and the sequence is cut up into equal segments [shownbelow the axis in FIG. 11(e)], all consisting of substantially the samenumber of digitization elements, and all starting substantially the samenumber L of digitization elements to the left of the respectivereference point, such number L being chosen to result in segments, eachof which (whenever possible) contains an entire decay curve not splitbetween adjacent segments, as illustrated schematically in FIG. 11(e).The segment length is chosen to closely match the excitation pulserepetition period.

Graph 1160 in FIG. 11(f) depicts the following step of signal processingby showing each of the decay curve segments 1151-1156 from FIG. 11(e)(A, B, C, . . . ) added coherently on top of each other, with therespective temporal relationships within each segment unchanged. Suchadding is performed coherently on the basis of individual digitizationelements: The values of the first digitization index (#0) in everysegment are added together (A0+B0+C0 . . . ), the values of the seconddigitization index (#1) in every segment are added together (A1+B1+C1 .. . ), and so on for all digitization indices in all segments. Theresult is a “supercurve” [bold curve 1165 in FIG. 11(f)], where eachdigitization index has a value equal to the sum of all the correspondingdigitization indices from all segments. The supercurve is then convertedto a semilog scale for further processing.

This signal processing method removes incoherent noise contributionsfrom the result while boosting the contribution of signals coherent frompulse to pulse. The supercurve 1165 in graph 1160 of FIG. 11(f) maystill exhibit some degree of incoherent noise, which is to be expectedgiven the stochastic nature of the decay process and the presence ofvarious sources of measurement noise on the signals; however, thegeneral nature of the decay is expected to remain constant within agiven population of fluorophores, and the supercurve process is aimed atmaximizing the signal from such common decay while minimizing the effectof stray light signals, electronic noise and other events lackinginformation content germane to the analysis being carried out.

FIGS. 12(a) and 12(b) illustrate exemplary embodiments of several stepsof an analysis method of the current invention. Both FIGS. 12(a) and12(b) display curves plotted on a semilog scale of the natural (or,alternatively, the base-10) logarithm axis of measured intensity vs. thelinear axis of time. In graph 1250 of FIG. 12(a) the excitation pulse(bold solid curve 1201) and the resulting emission supercurve due, e.g.,to fluorescence (dashed curve 1210) are each normalized to unity peakvalue; on the shown logarithmic scale, a linear value of one correspondsto the logarithmic value of zero. The supercurve 1210 shown is obtainedas described above in reference to FIGS. 11(a)-(f) for supercurve 1165.For illustrative purposes, the supercurve 1210 in graph 1250 of FIG.12(a) is shown as comprising three distinct lifetime components [eachalso referred to herein as “component,” “lifetime,” “lifetime value,”“1/e value,” “time constant,” “decay constant,” or “exponential decay”,and corresponding to the value of Tin the standard exponential decayformula I(t)=I₀ exp(−t/τ), where I₀ is the starting intensity and I(t)is the intensity after a time t]: τ_(a), τ_(b), and τ_(c). In thisexample, τ_(a) is the smallest time constant of the three, τ_(c) is thelargest, and τ_(b) is intermediate between the two. The relative valuesof τ_(a), τ_(b), and τ_(c) are reflected in the slopes of the threebranches a (1221), b (1222), and c (1223) of the supercurve 1210: theslope of branch a 1221 is steepest, the slope of branch c 1223 ismildest, and the slope of branch b 1222 is intermediate between the two.The slope of a branch on a semilog plot of the kind depicted in FIGS.12(a) and 12(b) is inversely proportional to the value of thecorresponding time constant. The three branches 1221-1223 of thesupercurve 1210 in FIG. 12(a) are defined as follows: The first branch a1221 begins at the peak 1231 of the supercurve and ends at the first“knee” 1232 of the supercurve (where by “knee” is meant a substantialchange in slope, indicated by an open circle); the second branch b 1222begins at the first knee 1232 and ends at the next knee (the next opencircle 1233); the third branch c 1223 begins at this next knee 1233 andends at 1234 where the supercurve meets the measurement noise floor(schematically indicated in FIG. 12(a) by the time axis t). The slope ofeach branch is defined as customary as the ratio of the ordinate and theabscissa over a portion of or the entire branch: e.g., for branch b, theslope value is s_(b)=y_(b)/t_(b). The time constant corresponding tosuch slope is then obtained by the reciprocal of the slope:τ_(b)=1/s_(b).

It will be appreciated that when dealing with real measurements subjectto, for instance, noise, background, uncertainty, instrument error ordrift, component variability, and environmental effects, there may bedepartures, sometimes substantial, from the illustrations and depictionspresented here. Even when such effects are low or minimized, othereffects may act to mask, distort, alter, modify, or otherwise change therelationships among the various mathematical and physical quantitiesmentioned here. As one example, the noise floor where the supercurve inFIG. 12(a) starts and ends may be higher in certain cases and lower inothers, depending on several factors, including the ones just mentioned.The variability in the noise floor may affect the determination of oneor more of the slopes of the branches of the supercurve. Likewise, theprecise location of a knee between two branches on the supercurve may besubject to uncertainty depending on the level of residual noise on thesupercurve. Another example of the distortion created by physicaleffects is shown in FIG. 12(a) where branch a 1221 is shown as beginningat the peak 1231 of the supercurve 1210, however the slope of this firstbranch does not immediately converge onto a stable value due to theroll-off from the peak. The degree of roll-off is dependent on the shapeof the excitation pulse, the value of the first-branch lifetime, andother factors. These effects notwithstanding, it is one object of thepresent invention to minimize the impact of such effects. Constructionof the supercurve from a number of individual pulse signals, with itsattendant improvement in signal to noise, is one element thatcontributes to such minimization.

Another element is the relative simplicity in the extraction of desiredparameters, such as the values of the time constants, from a supercurve.This is illustrated by graph 1280 in FIG. 12(b). Graph 1280 shows adetail 1211 of the supercurve 1210 of FIG. 12(a), where branch a 1281(corresponding to branch a 1221 in graph 1250) ends and branch b 1282(corresponding to branch b 1222 in graph 1250) begins. (The graph hasbeen offset and rescaled in both abscissa and ordinate for illustrativepurposes.) The two branches meet at the knee 1292 indicated by the opencircle, corresponding to knee 1232 in graph 1250. Also plotted in FIG.12(b) are the individual digitized points of the supercurve, indicatedby small filled circles with solid drop lines to the time axis. Theprocess step of determining the location of a knee (that is, thetransition between one branch where a value of lifetime dominates, toanother branch where a different value of lifetime dominates) comprisescomputing differences between successive values of the digitizedsupercurve. Four such difference for branch a are shown as δ_(a). Whereresidual noise on the supercurve is minimized, the value of δ_(a) fromdigitized point pair to digitized point pair will show little variation.Once the knee is crossed, however, the next computed difference willjump to δ_(b), and successive differences will once again remainsubstantially uniform around this new value. For one of the mainobjectives of the present invention, namely the provision of highlymultiplexed means of particle analysis and sorting, it is not criticalthat the depicted successive values of δ_(a) be rigorously constant, northose of δ_(b); it is merely sufficient that δ_(a) be different enoughfrom δ_(b) to enable detection of the slope change at the indicated kneepoint. Sufficient difference between δ_(a) and δ_(b) is related to theprecision and accuracy of the measurement system, the number, types, andseverity of noise or error sources, and other factors. Detection of adiscontinuous change in slope, however, is intrinsically simpler,instrumentally and computationally, than the absolute determination ofthe value of a slope.

Once a knee is found, the process continues until the entire supercurveis examined. The location of each knee, together with the location ofthe start of the first branch and the end of the last branch, define allthe branches of the supercurve. The next processing step involvescomputing the average slope for each branch, which was described abovein reference to FIG. 12(a), and from such slope values the timeconstants of each branch are calculated. The following processing stepinvolves allocating each branch to one of a set of predeterminedlifetime (or time constant) bins. As illustrated in FIGS. 5 and 6, oneaspect of the present invention is the provision of a limited set oflifetime bins, where the lifetime within any one bin is allowed to varysomewhat, as long as the variation is not greater than the differencebetween neighboring bins. For the purpose of analyzing a supercurve anddetermining what lifetimes gave rise to the signals from which thesupercurve was constructed, it is sufficient to establish (1) which ofthe lifetime bins was present in the measured particle or event (i.e.,what fluorophores or other molecular species were present with afluorescence decay value within the range of any one of the providedlifetime bins), and (2) the degree of relative contribution of eachdetected lifetime. For (1), the set of time constants computed from thebranches of the supercurve as described above is compared to the set ofallowed lifetime bins. In some cases there will be as many separatedetected branches in a supercurve as there are bins: this would be thecase for FIG. 12(a), for example, if the number of allowed bins were 3.In other cases there will be fewer branches, indicating that a certainbin was not present (i.e., that no fluorophore or molecular species witha lifetime in the range of values of that bin was detected). Bycomparing the set of measured time constants with the set of allowedbins, a determination is made as to which bins are present in themeasurement. Determination of the relative contribution of each detectedlifetime (now associated with one of the allowed lifetime bins) isperformed by comparing the values of the ordinates of each branch [thevalues y_(a), y_(b), and y_(c) in graph 1250 of FIG. 12(a)] with acalibration look-up table generated during manufacture of the apparatus.Such calibration look-up table is created by generating supercurves withknown inputs, i.e., with 100% of one lifetime bin, 100% of another, andso on for all the lifetime bins selected to be available on theapparatus; then with varying mixtures of bins, such as, e.g., 10% of bin1 and 90% of bin 2, 20% of bin 1 and 80% of bin 2, and so on until 90%of bin 1 and 10% of bin 2; repeating this for each pair of binsavailable on the apparatus. The resulting data provides the look-uptable to compare measured lifetime ordinates (e.g., y_(a), y_(b), andy_(c)) with, and thereby determine the relative contributions of eachdetected lifetime.

FIGS. 13(a) and 13(b) illustrate exemplary embodiments of two steps ofan analysis and sorting method of the current invention. In FIGS. 13(a)and (b), the relative orientation of fluid flow, light propagation, andtransverse directions is shown as the set of axes x, z, and y,respectively. The assignment of the axes and directions is similar tothat in FIGS. 9 and 10, however the orientation of the axes with respectto the page is rotated as compared to FIGS. 9 and 10, with the lightpropagation and flow directions being in the plane of the page in FIGS.13(a) and (b). Each of the two figures shows a schematic representationof a side view of the interrogation region 1331 and sorting region 1332of the flowcell 1300. The focusing region of the flowcell, if provided,e.g., by hydrodynamic means, is to the left of the picture; the samplecore stream 1330, surrounded by the sheath fluid 1320, comes in from theleft and flows towards the right. The sheath fluid 1320 is bounded bythe inner walls of the flowcell 1300, and the sample core stream 1330 isbounded by the sheath fluid 1320. In the interrogation region 1331 atleft, one or more beams of pulsed optical energy 1340 are delivered tothe flowcell by relay/focusing optics and intersect the sample corestream 1330. In the sorting region 1332 at right, one or more actuators(shown in the picture as actuator 1380) are provided in contact with ornear the flowcell, positioned in such a way as to overlay the positionof the sample core stream 1330.

FIG. 13(a) shows a first time step in the processing of a sample wherebya single particle 1355 in the sample core stream 1330 enters theinterrogation region 1331 (where the beam or beams 1340 intersect thesample core stream 1330). The light-particle interaction generates lightsignals as described above in reference to FIG. 9 or 10, which lightsignals are collected and relayed to one or more detectors. Thedetector(s) record the optical interaction signals generated by theparticle 1355, and convey that information to the signal processing unitas illustrated schematically in FIG. 8. As described above in referenceto FIG. 8, the processing unit uses that information to produce, ifcertain predetermined criteria are met, a triggering signal for anactuator driver, which driver in turn activates the actuator 1380 inFIG. 13(a). FIG. 13(b) shows a second time step in the processing of thesample whereby the particle 1355 detected in the step depicted in FIG.13(a), after following path 1365 in the flowcell along direction x,arrives at a point in the vicinity of the actuator 1380 in the sortingregion 1332 of the flowcell. The design of the flowcell, of the opticallayout of the actuator, and of the detection, processing, and controlelectronics is such that the actuator is activated as such a time whenthe passing particle is calculated, estimated, predicted, or found, uponcalibration or determined empirically during instrument design orassembly, to be nearest to a position where activation of the actuatorresults in the desired diversion of the core stream to one of the one ormore sorting channels. The timing of the triggering signal (i.e., therelative delay from particle detection to sorting actuation) is designedto take into account both the average velocity of fluid flow in theflowcell and its spatial profile across the flowcell cross-section,according to the characteristics of Poiseuille flow known in the art andas modified based on empirical or modeling information.

In FIGS. 14(a) and (b), 15(a) and (b), 16(a) and (b), and 17(a)-(d), therelative orientation of fluid flow, light propagation, and transversedirections is shown as the set of axes x, z, and y, respectively. Theassignment of the axes and directions is similar to that in FIGS. 9 and10, however the orientation of the axes with respect to the page isrotated as compared to FIGS. 9 and 10, with the fluid flow andtransverse directions being in the plane of the page in FIGS. 14(a) and(b), 15(a) and (b), 16(a) and (b), and 17(a)-(d). The cross-sectionalplane depicted in FIGS. 14(a) and 14(b), 15(a) and (b), 16(a) and (b),and 17(a)-(d) is the plane that contains the sample core stream.

FIGS. 14(a) and 14(b) illustrate one embodiment of two states of theparticle analysis and sorting method of the current invention. Each ofthe two figures shows a schematic representation of a cross-sectionalview of the sorting region of the flowcell. Similarly to the situationdepicted in FIGS. 13(a) and (b), the focusing region of the flowcell,e.g., by hydrodynamic means, if provided, is to the left of the picture;the sample core stream 1430, surrounded by the sheath fluid 1420, comesin from the left and flows towards the right. The sheath fluid 1420 isbounded by the inner walls of the flowcell 1400, and the sample corestream 1430 is bounded by the sheath fluid 1420. The flowcell 1400splits into two channels in the sorting region: the default sortingchannel 1446 and the sorting channel 1448. Actuator 1480 is depicted asembodied in, in contact with, or in proximity of the inner wall of theflowcell 1400 on the default sorting channel side. FIG. 14(a) shows theconfiguration of the default state, where with the actuator 1480 in theOFF state, a non-selected particle 1450 in the sample core stream 1430flows by design into the default sorting channel 1446. Similarly to thestate depicted in FIG. 13(b), FIG. 14(b) shows the configuration of thesorting state, where with the actuator 1480 in the ON state, a transientgas, vapor, or gas-vapor bubble, or a region of heated or cooled,less-dense sheath fluid 1495 is generated (by means including, forinstance, thermal means, electrolytic means, and gas injection means),which creates a localized flow diversion in the depicted cross-sectionalplane and in its vicinity, which diversion temporarily deflects thesample core stream 1431 into the sorting channel 1448, which sample corestream contains a particle 1455 detected upstream and automaticallyselected by analysis algorithms to trigger sorting actuation. Followingdeactivation of the actuator 1480, the transient gas, vapor, gas-vaporbubble or region of less-dense fluid 1495 shrinks or is cleared away,and the flow pattern returns to the original default state of FIG.14(a).

FIGS. 15(a) and 15(b) illustrate another embodiment of two states of aparticle analysis and sorting method of the current invention. It issimilar to the embodiment illustrated in FIGS. 14(a) and 14 (b), exceptin the design and nature of actuation. Here the actuator 1580 is locatedin proximity to an expandable chamber 1597 adjacent to the flowcellinner wall and separated from the sheath fluid 1520 by a flexiblemembrane 1596. With the actuator 1580 in the OFF or default state asshown in FIG. 15(a), the expandable chamber 1597 is in its defaultconfiguration at a pressure designed to match the pressure of the fluidinside the flowcell at the location of the membrane, resulting in a flatshape of the membrane to match the shape of the flowcell inner wall, anda non-selected particle 1550 in the sample core stream 1530 flows bydesign into the default sorting channel 1546. With the actuator 1580 inthe ON or sorting state as shown in FIG. 15(b), the expandable chamber1597 is pressurized (by means including, for instance, thermal means,mechanical means, hydraulic and gas injection means) to a higherpressure than in the default configuration; this pressure differentialcauses the membrane 1596 to flex into the flowcell until a newequilibrium is reached. The bulging membrane causes the flow pattern toshift in a similar way to that previously shown for FIG. 14(b),resulting in the sample core stream 1531 being temporarily diverted intothe sorting channel 1548, which sample stream contains a particle 1555detected upstream and automatically selected by analysis algorithms totrigger sorting actuation. Following deactivation of the actuator 1580,the expandable chamber 1597 is allowed to or made to return to itsdefault pressure state, the membrane 1596 returns to its default flatshape, and the flow pattern returns to the original defaultconfiguration of FIG. 15(a).

FIGS. 16(a) and 16(b) illustrate yet another embodiment of two states ofa particle analysis and sorting method of the current invention. It issimilar to the embodiment illustrated in FIGS. 15(a) and 15(b), exceptin the design of actuation. Sorting actuation here is realized by meansof two actuators, positioned on opposite sides of the flowcell, eachactuator being located in proximity to expandable/compressible chambers(1697 for the default side and 1699 for the sort side) adjacent to theflowcell inner wall and separated from the sheath fluid 1620 by aflexible membrane (1696 for the default side and 1698 for the sortside). In the default state, depicted in FIG. 16(a), the expandablechambers 1697 and 1699 of both the default-side and sort-side actuatorsare in their default configuration at pressures designed to match thepressure of the fluid inside the flowcell at the location of themembranes 1696 and 1698, resulting in flat shapes of the membranes tomatch the shape of the flowcell inner walls. In this non-sorting state,a non-selected particle 1650 in the sample core stream 1630 flows bydesign into the default sorting channel 1646. In the sorting state,depicted in FIG. 16(b), the expandable chamber 1697 of the default-sideactuator 1680 is pressurized (by means including, for instance, heatingmeans, mechanical means, hydraulic means, and gas injection means),through actuation, in a similar way as depicted in reference to FIG.15(b); this pressure differential with respect to the local pressure inthe sheath fluid causes the membrane 1696 to bulge into the flowcelluntil a new equilibrium is reached. Simultaneously, the compressiblechamber 1699 of the sorting side actuator 1681 is depressurized (bymeans including, for instance, cooling means, mechanical means,hydraulic means, and gas aspiration means), through activation ofactuator 1681, to a lower pressure than in the default configuration;this pressure differential with respect to the local pressure in thesheath fluid causes the membrane 1698 to flex away from the flowcelluntil a new equilibrium is reached. The combination of the inwardlybulging default-side membrane 1696 and the outwardly flexing sort-sidemembrane 1698 causes the flow pattern to shift in a similar way to thatpreviously shown for FIGS. 14(b) and 15(b), resulting in the sample corestream 1631 being temporarily diverted into the sorting channel 1648,which sample stream contains a particle 1655 detected upstream andautomatically selected by analysis algorithms to trigger sortingactuation. Following deactivation of the actuator pair, both thedefault-side and the sort-side expandable/compressible chambers 1697 and1699 are allowed to or made to return to their default pressure states,both the default-side and the sort-side membranes 1696 and 1698 returnto their default flat shapes, and the flow pattern returns to theoriginal default configuration of FIG. 16(a).

FIGS. 17(a)-(d) illustrate a multi-way sorting embodiment of a particleanalysis and sorting method of the current invention. Each of the fourfigures shows a schematic representation of a cross-sectional view ofthe sorting region of the flowcell. The configuration is similar to thatdepicted in reference to FIGS. 14(a) and (b), except that instead of asingle sorting channel, a plurality of sorting channels 1741-1744 isprovided along a transverse direction y. One advantage of thisembodiment is the ability to have a plurality of different receptaclesinto which the sample may be sorted, depending on the result of theupstream analysis by the interrogating light beam, the signal detectors,and associated electronic and logic trigger circuitry. For example, thesignals detected in response to the upstream interrogation of the samplemay indicate that a particle, e.g., particle 1751, was detected with acertain set A of properties targeted for selection (e.g., the presenceof surface antigens or intracellular markers associated with certainkinds of cancer cells). It may be desirable to sort particles havingthese properties into a certain collection receptacle, e.g., oneprovided to receive the outflow from sorting channel 1741, asillustrated in FIG. 17(b). Another particle, e.g., particle 1752, mayflow past the interrogation point and produce signals that indicate thepresence of a different set B of properties targeted for selection(e.g., the presence of surface antigens or intracellular markersassociated with certain kinds of stem cells). It would be desirable tosort particles like particle 1752 having set-B properties into adifferent receptacle from that designed for collection of particleshaving set-A properties: e.g., a receptacle provided to receive theoutflow from sorting channel 1742, as illustrated in FIG. 17(c).Likewise for yet another set D of properties, particles like particle1754 detected as having those properties, and a sorting channel 1744designed to flow into a receptacle to collect such particles.Accordingly, the embodiment illustrated in FIGS. 17(a)-(d) provides anexample of such a multi-way sorting capability of the current invention,with a number of sorting channels 1741-1744 in addition to the defaultsorting channel 1746. FIGS. 17(a)-(d) exemplarily show four such sortingchannels explicitly. It will be apparent to those skilled in the artthat additional configurations having more or less than four sortingchannels, in addition to the default sorting channel, do not depart fromthe scope of the disclosed invention.

Each of the sorting channels 1741-1744 (as well as the default sortingchannel 1746) may optionally be connected with a receiving receptacledesigned to collect the fluid flow from the respective channel. Theselection of a particular sorting channel (or of the default sortingchannel) as the target for reception of a desired sorted portion of thesample core stream is effected by actuation of actuator 1780. In atwo-way sort there are two principal sorting states, which can bedescribed as OFF (default) and ON (sorting) as described above inrelation to FIGS. 14(a)-(b), 15(a)-(b), and 16(a)-(b). In a multi-waysort, on the other hand, there generally can be as many sorting statesas there are sorting “ways” or possible sorting channels. With referenceto FIGS. 17(a)-(d), five possible sorting channels are indicated (thedefault sorting channel 1746 plus four sorting channels 1741-1744);accordingly, this is referred to as a five-way sort. An actuationprocess is provided to result in different degrees of deflection of thesample core stream portion, corresponding to the selection of differentintended sorting channels.

In FIG. 17(a) actuator 1780 is depicted as embodied in, in contact with,or in proximity of the inner wall of the flowcell 1700 on the defaultsorting channel side. Similarly to the state depicted in FIG. 14(a),FIG. 17(a) shows the configuration of the default state, where with theactuator 1780 in the OFF state, a non-selected particle 1750 in thesample core stream 1730 flows by design into the default sorting channel1746. Similarly to the state depicted in FIG. 14(b), FIGS. 17(b)-(d)show the configurations of various sorting states, where with theactuator 1780 in the ON state at levels 1, 2, and 4, respectively,transient regions 1791, 1792, and 1794, respectively (comprising, forinstance, a gas, vapor, gas-vapor bubble, or a less-dense region ofsheath fluid), are generated (by means including, for instance, thermalmeans, electrolytic means, and gas injection means), which createrespective localized flow diversions in the depicted cross-sectionalplane and in its vicinity, which diversions temporarily deflect thesample core stream into configurations 1731, 1732, and 1734,respectively, and cause the corresponding particles 1751, 1752, and1754, respectively, to flow into the respective sorting channels 1741,1742, and 1744. Following deactivation of the actuator, the transientgas bubble shrinks or is cleared away, and the flow pattern returns tothe original default state of FIG. 17(a). Not shown is the configurationof a sorting state intermediate to the sorting states of FIGS. 17(c) and17(d), corresponding to an actuation level 3, whereby a transient regionof a size intermediate between that of regions 1792 and 1794 temporarilydiverts the sample core stream into sorting channel 1743.

Throughout this disclosure the term “default sorting channel” isassociated with an OFF state of an actuator, signifying a passive statein which no particle sorting is performed, and in which the sample corestream and particles therein are typically outflowed and discarded asundesired waste. The term “sorting channel” is associated with an ONstate of an actuator, signifying an activated state of an actuator, inwhich active sorting of a desired particle is performed. While for someembodiments this may be a preferred configuration, the invention is notso limited, and included under the scope of the invention areembodiments where a passive state of an actuator is associated withcollection of desired particles, and an active state of an actuator isassociated with generation of a waste stream of undesired particles fromthe particle analyzer/sorter.

Referring to FIG. 18(b), a flow chart is provided that describes asequence of principal steps involved in the performance of the step ofparticle analysis in accordance with an embodiment of the presentinvention. A first step 1840 involves the generation of one or moretrains of optical pulses (or other modulated output of light from one ormore sources) for optical interrogation of particles in a sample. Asecond step 1842 involves the presentation of a sample, or theintroduction of a sample, to the apparatus by a user or operator. Athird, optional, step 1844 involves the mixing, reaction, and incubationof the sample with one or more reagents, which reagents may be preloadedonboard the apparatus or may be introduced by the user or operator. Afourth step 1846 involves the formation, by means of hydrodynamicfocusing of the sample by sheath fluid, of a core stream of particlesflowing essentially in single file in the microchannel portion of theflowcell for optical interrogation. A fifth step 1848 involves theinterrogation, by optical interaction, of a single particle in thesample core stream by the one or more trains of optical pulses,resulting in the generation of optical interaction signals. A sixth step1850 involves the collection of the optical interaction signals, theoptical filtering of the collected optical signals, and the spectralisolation of the filtered optical signals. A seventh step 1852 involvesthe detection of the spectrally isolated optical signals, thetransduction of said signals into analog electrical signals, thedigitization of the analog electrical signals into digital signals, andthe processing of the digital signals. An eighth step 1854 involves thefurther application of digital signal processing algorithms to thedigital signals corresponding to each isolated spectral band so as toisolate the separate contributions of one or more fluorescence lifetimecomponents to each signal. A ninth optional step 1856 involves theaveraging of lifetime signals coming from different pulses but alloriginating from the same particle under interrogation. A tenth step1858 involves the recording and storage of the detected and processedsignal parameters, such as, without limitation, fluorescence intensityin one or more spectral bands, one or more fluorescence lifetime valuesin each of the one or more spectral bands, phase shift, scatteringintensity, and absorption. An eleventh step 1860 involves a decision,which may be automated or may be presented by the system, through aprocessing unit, to the user or operator as a call for action, onwhether to analyze additional particles; if the choice is positive, themethod workflow returns to the fifth step above; if the choice isnegative, the method workflow continues to the next (twelfth) stepbelow. A twelfth optional step 1862 involves the classification of aportion or a totality of the events detected and analyzed according tocertain criteria (which may include, without limitation, entitiescommonly referred to in the art as “triggers,” “thresholds,” and“gates”), which may be predetermined and preloaded into the apparatus ormay be selected or modified or created by the user. A thirteenth step1864 involves the presentation to the user or operator of the processeddata (which may include, without limitation, the raw detectedtime-varying signals, a list of detected particle-interrogation events,and graphs or plots of detected events displayed according tocharacteristics such as, e.g., fluorescence lifetime, fluorescenceintensity, and scattering) by means of a user interface such as, e.g., ascreen, a computer monitor, a printout, or other such means.

FIG. 19 shows a block diagram of an exemplary embodiment of a dataprocessing system 1900 to provide a particle analysis and sorting systemas described herein. In an embodiment, data processing system 1900 is apart of the control system to perform a method that includes providinglight pulses; providing a sample for analysis; exposing the sample tothe light pulses; detecting optical decay curves; and extracting timeconstants from the optical decay curves, as described herein. In someembodiments, data processing system 1900 is represented by any one ofsignal processing units 790, 890, 990 and 1090 depicted in FIGS. 7, 8,9, and 10, respectively, and further optionally incorporates any one ofdata storage units 792 and 892 depicted in FIGS. 7 and 8, respectively.

Data processing system 1900 includes a processing unit 1901 that mayinclude a microprocessor or microcontroller, such as Intelmicroprocessor (e.g., Core i7, Core 2 Duo, Core 2 Quad, Atom), SunMicrosystems microprocessor (e.g., SPARC), IBM microprocessor (e.g., IBM750), Motorola microprocessor (e.g., Motorola 68000), Advanced MicroDevices (“AMD”) microprocessor, Texas Instrument microcontroller, andany other microprocessor or microcontroller.

Processing unit 1901 may include a personal computer (PC), such as aMacintosh® (from Apple Inc. of Cupertino, Calif.), Windows®-based PC(from Microsoft Corporation of Redmond, Wash.), or one of a wide varietyof hardware platforms that run the UNIX operating system or otheroperating systems. For at least some embodiments, processing unit 1901includes a general purpose or specific purpose data processing systembased on Intel, AMD, Motorola, IBM, Sun Microsystems, IBM processorfamilies, or any other processor families. As shown in FIG. 19, a memory1903 is coupled to the processing unit 1901 by a bus 1923. Memory 1903has instructions and data 1904 stored thereon which when accessed byprocessing unit 1901 cause the processing unit 1901 to perform methodsto provide highly multiplexed particle analysis or lifetime analysis,and optionally sorting, as described herein.

Memory 1903 can be dynamic random access memory (“DRAM”) and can alsoinclude static random access memory (“SRAM”). A bus 1923 couplesprocessing unit 1901 to memory 1903 and also to a non-volatile storage1909 and to a display controller 1905 (if a display is used) and toinput/output (I/O) controller(s) 1911. Display controller 1905 controlsin the conventional manner a display on a display device 1907 which canbe a cathode ray tube (CRT), a liquid crystal display (LCD), alight-emitting diode (LED) monitor, a plasma monitor, or any otherdisplay device. Input/output devices 1917 can include a keyboard, diskdrives, printers, a scanner, a camera, and other input and outputdevices, including a mouse or other pointing device. I/O controller 1911is coupled to one or more audio input devices 1913 such as, for example,one or more microphones.

Display controller 1905 and I/O controller 1911 can be implemented withconventional well-known technology. An audio output 1915 such as, forexample, one or more speakers, may be coupled to I/O controller 1911.Non-volatile storage 1909 is often a magnetic hard disk, an opticaldisk, or another form of storage for large amounts of data. Some of thisdata is often written, by a direct memory access process, into memory1903 during execution of software in data processing system 1900 toperform methods described herein.

One of skilled in the art will immediately recognize that the terms“computer-readable medium” and “machine-readable medium” include anytype of storage device that is accessible by processing unit 1901. Dataprocessing system 1900 can interface to external systems through a modemor network interface 1921. It will be appreciated that modem or networkinterface 1921 can be considered to be part of data processing system1900. This interface 1921 can be an analog modem, ISDN modem, cablemodem, token ring interface, satellite transmission interface, Wi-Fi,Bluetooth, cellular network communication interface, or other interfacesfor coupling a data processing system to other data processing systems.

It will be appreciated that data processing system 1900 is one exampleof many possible data processing systems which have differentarchitectures. For example, personal computers based on an Intelmicroprocessor often have multiple buses, one of which can be aninput/output (I/O) bus for the peripherals and one that directlyconnects processing unit 1901 and memory 1903 (often referred to as amemory bus). The buses are connected together through bridge componentsthat perform any necessary translation due to differing bus protocols.

Network computers are another type of data processing system that can beused with the embodiments as described herein. Network computers do notusually include a hard disk or other mass storage, and the executableprograms are loaded from a network connection into memory 1903 forexecution by processing unit 1901. A typical data processing system willusually include at least a processor, memory, and a bus coupling thememory to the processor.

It will also be appreciated that data processing system 1900 can becontrolled by operating system software which includes a file managementsystem, such as a disk operating system, which is part of the operatingsystem software. Operating system software can be the family ofoperating systems known as Macintosh® Operating System (Mac OS®) or MacOS X® from Apple Inc. of Cupertino, Calif., or the family of operatingsystems known as Windows® from Microsoft Corporation of Redmond, Wash.,and their associated file management systems. The file management systemis typically stored in non-volatile storage 1909 and causes processingunit 1901 to execute the various acts required by the operating systemto input and output data and to store data in memory, including storingfiles on non-volatile storage 1909.

In various embodiments, hardwired circuitry may be used in combinationwith software instructions to implement methods described herein. Anon-transitory machine-readable medium can be used to store software anddata which when executed by a data processing system causes the systemto perform various methods described herein. This executable softwareand data may be stored in various places including for example ROM,volatile RAM, non-volatile memory, and/or cache. Portions of thissoftware and/or data may be stored in any one of these storage devices.

Thus, a machine-readable medium includes any mechanism that provides(i.e., stores and/or transmits) information in a form accessible by amachine (e.g., a computer, network device, or any device with a set ofone or more processors, etc.). For example, a machine-readable mediumincludes recordable/non-recordable media (e.g., read only memory (ROM);random access memory (RAM); magnetic disk storage media; optical storagemedia; flash memory devices; and the like).

It will be further appreciated that data processing system 1900 may befunctionally implemented by allocating several of its functions todistributed units or modules separate from a central system. In someembodiments, some or all of the signal processing functions as depicted,e.g., in FIGS. 7-10, illustrated in FIGS. 11(a)-(f) and 12(a)-(b), anddescribed in FIGS. 18(a)-(c), may be performed by signal processingunits or modules physically separate from data processing system 1900,yet connected with it for performance of other functions, such as, e.g.,input/output, display, data storage, memory usage, bus usage, additionalsignal processing functions, and both specific-purpose andgeneral-purpose data processing functions. In some embodiments, some orall of the data storage functions as depicted, e.g., in FIGS. 7-8,illustrated in FIGS. 11(a)-(f) and 12(a)-(b), and described in FIGS.18(a)-(c), may be performed by data storage units or modules physicallyseparate from data processing system 1900, yet connected with it asdescribed above. In some embodiments, some or all of the signalprocessing functions mentioned may be performed by processing unit 1901internal to data processing system 1900, and in some embodiments some orall of the data storage functions mentioned may be performed bynon-volatile storage unit 1909 and/or memory unit 1903 internal to dataprocessing system 1900.

The methods as described herein can be implemented using dedicatedhardware (e.g., using Field Programmable Gate Arrays, Digital SignalProcessing chips, or Application Specific Integrated Circuits) or sharedcircuitry (e.g., microprocessors, microcontrollers, single-boardcomputers, standalone computers, or cloud-based processors on remoteservers) under control of program instructions stored in amachine-readable medium. The methods as described herein can also beimplemented as computer instructions for execution on a data processingsystem, such as system 1900 of FIG. 19.

It will be appreciated by those skilled in the art that aspects of thepresent invention, while illustrated with reference to applications toparticle analysis and sorting and particularly to flow cytometry, alsopresent advantages in other application areas. The concept of lifetimebinning as a means to simplify the performance of lifetime measurementsand thereby enable higher degree of multiplexing than hithertopractical, for example, is also advantageous to the field of imaging, inparticular to the field of microscopy, and more particularly to thefield of fluorescence microscopy. Whereas in a flow cytometer an “event”is defined as the passage of a particle through the interrogation area,in microscopy the roughly equivalent element is a “pixel,” defined asthe smallest resolvable unit of an image. Spectral spillover andcrosstalk is a problem in fluorescence microscopy just as it is aproblem in flow cytometry, and the present invention offers a solutionto both by providing a greater degree of multiplexing, a reduced levelof spectral spillover, or a combination of the two. The presentinvention admits of implementation within the framework of afluorescence microscope in ways that parallel very closely the specificexamples given in the case of flow-based particle analysis. A microscopyapplication of the present invention, for example, would rely on asystem configuration very similar to that of FIG. 7, with the fluidelements 740, 742, 700, and 740 replaced by a suitable sample holder,such as are well known in the art, for exposure of the sample to thebeam; and similarly for FIGS. 9 and 10. In other words, adaptation ofthe present invention to the field of microscopy is fully within thescope of this disclosure, given the descriptions of the novel apparatusand methods herein. One specific application of fluorescence microscopythat would benefit from the present invention is in vivo imaging, suchas, e.g., methods and apparatuses used for medical diagnostics. Theseinclude the analysis and diagnosis of externally optically accessibleorgans, such as the skin and the eye, as well as organs opticallyaccessible through the use of endoscopes, such as the respiratory tract,the gastrointestinal tract, and, in the context of surgery, any otherorgan or part of the body. As in the case of laboratory-basedfluorescence microscopy, adaptation of the apparatuses and methodsdescribed herein is entirely within the scope of the present invention,requiring only minor modifications of the apparatus and process stepsfrom the illustrative examples that are provided. The usefulness of thepresent invention is therefore not to be circumscribed to the examplesand figures provided, but extends to the full scope of what is claimed.

A method of analyzing particles in a sample using a particle analyzer isdisclosed, comprising the steps of:

-   -   providing a source of a beam of pulsed optical energy;    -   providing a sample holder configured to expose a sample to the        beam;    -   providing a detector, the detector comprising a number of        spectral detection channels, the channels being sensitive to        distinct wavelength sections of the electromagnetic spectrum and        being configured to detect optical signals resulting from        interactions between the beam and the sample, the channels being        further configured to convert the optical signals into        respective electrical signals;    -   providing a first optical path from the source of the beam to        the sample;    -   providing a second optical path from the sample to the detector;    -   providing a signal processing module;    -   exposing the sample to the beam, and    -   using the signal processing module for:    -   receiving the electrical signals from the detector;    -   mathematically combining individual decay curves in the        electrical signals into a decay supercurve, said supercurve        comprising a number of components, each component having a time        constant and a relative contribution to the supercurve;    -   extracting time constants from the supercurve; and    -   quantifying the relative contribution of individual components        to the supercurve.

A method of analyzing and sorting particles in a sample using a particleanalyzer/sorter is disclosed, comprising the steps of:

-   -   providing an internally modulated laser as a source of a beam of        pulsed optical energy;    -   providing a flowcell configured as an optical excitation chamber        for exposing to the beam a sample comprising a suspension of        particles and for generating optical signals from interactions        between the beam and the particles;    -   providing a detector, the detector comprising a number of        spectral detection channels, the channels being sensitive to        distinct wavelength sections of the electromagnetic spectrum and        being configured to detect fluorescence optical signals        resulting from interactions between the beam and the particles        in the sample, the channels being further configured to convert        the optical signals into respective electrical signals;    -   providing a first optical path from the source of the beam to        the sample;    -   providing a second optical path from the sample to the detector;    -   providing a flow path for the suspension of particles;    -   providing connections between the flowcell and each of the flow        path, the first optical path, and the second optical path;    -   providing a signal processing module comprising one of an FPGA,        a DSP chip, an ASIC, a CPU, a microprocessor, a microcontroller,        a single-board computer, a standalone computer, and a        cloud-based processor;    -   exposing the particles in the sample to the beam;    -   using the signal processing module for:    -   receiving the electrical signals from the detector;    -   mathematically combining individual decay curves in the        electrical signals into a decay supercurve, said supercurve        comprising a number of components, each component having a time        constant and a relative contribution to the supercurve;    -   extracting time constants from the supercurve; and    -   quantifying the relative contribution of individual components        to the supercurve;    -   providing a particle sorting actuator connected with the flow        path, based on at least one flow diversion in the flow path, and        further based on one of a transient bubble, a pressurizable        chamber, a pressurizable/depressurizable chamber pair, and a        pressure transducer;    -   providing an actuator driver connected with the actuator, the        driver being configured to receive actuation signals from the        signal processing module;    -   providing at least one particle collection receptacle; and    -   collecting at least one particle from the suspension of        particles in the particle collection receptacle.

A method of analyzing particles in a sample using a particle analyzer isdisclosed, comprising the steps of:

-   -   providing a source of a beam of pulsed optical energy;    -   providing a sample holder configured to expose a sample to the        beam;    -   providing a detector, the detector comprising a number of        spectral detection channels, the channels being sensitive to        distinct wavelength sections of the electromagnetic spectrum and        being configured to detect optical signals resulting from        interactions between the beam and the sample, the channels being        further configured to convert the optical signals into        respective electrical signals;    -   providing a first optical path from the source of the beam to        the sample;    -   providing a second optical path from the sample to the detector;    -   providing a signal processing module;    -   exposing the sample to the beam, and    -   using the signal processing module for:    -   receiving the electrical signals from the detector;    -   mathematically combining individual decay curves in the        electrical signals into a decay supercurve, said supercurve        comprising a number of components, each component having a time        constant and a relative contribution to the supercurve;    -   allocating individual components of the supercurve to discrete        bins of predetermined time constants; and    -   quantifying the relative contribution of individual components        to the supercurve.

A method of analyzing and sorting particles in a sample using a particleanalyzer/sorter is disclosed, comprising the steps of:

-   -   providing an internally modulated laser as a source of a beam of        pulsed optical energy;    -   providing a flowcell configured as an optical excitation chamber        for exposing to the beam a sample comprising a suspension of        particles and for generating optical signals from interactions        between the beam and the particles;    -   providing a detector, the detector comprising a number of        spectral detection channels, the channels being sensitive to        distinct wavelength sections of the electromagnetic spectrum and        being configured to detect fluorescence optical signals        resulting from interactions between the beam and the particles        in the sample, the channels being further configured to convert        the optical signals into respective electrical signals;    -   providing a first optical path from the source of the beam to        the sample;    -   providing a second optical path from the sample to the detector;    -   providing a flow path for the suspension of particles;    -   providing connections between the flowcell and each of the flow        path, the first optical path, and the second optical path;    -   providing a signal processing module comprising one of an FPGA,        a DSP chip, an ASIC, a CPU, a microprocessor, a microcontroller,        a single-board computer, a standalone computer, and a        cloud-based processor;    -   exposing the particles in the sample to the beam;    -   using the signal processing module for:    -   receiving the electrical signals from the detector;    -   mathematically combining individual decay curves in the        electrical signals into a decay supercurve, said supercurve        comprising a number of components, each component having a time        constant and a relative contribution to the supercurve;    -   allocating individual components of the supercurve to discrete        bins of predetermined time constants; and    -   quantifying the relative contribution of individual components        to the supercurve;    -   providing a particle sorting actuator connected with the flow        path, based on at least one flow diversion in the flow path, and        further based on one of a transient bubble, a pressurizable        chamber, a pressurizable/depressurizable chamber pair, and a        pressure transducer;    -   providing an actuator driver connected with the actuator, the        driver being configured to receive actuation signals from the        signal processing module;    -   providing at least one particle collection receptacle; and    -   collecting at least one particle from the suspension of        particles in the particle collection receptacle.

In the foregoing specification, embodiments of the invention have beendescribed with reference to specific exemplary embodiments thereof. Itwill, however, be evident that various modifications and changes may bemade thereto without departing from the broader spirit and scope of theinvention. The specification and drawings are, accordingly, to beregarded in an illustrative rather than a restrictive sense.

What is claimed is:
 1. An apparatus for analyzing an optical signaldecay, comprising: a source of a beam of pulsed optical energy; a sampleholder configured to expose a sample to said beam; a detector, thedetector comprising a number of spectral detection channels, saidchannels being sensitive to distinct wavelength sections of theelectromagnetic spectrum and being configured to detect optical signalsresulting from interactions between said beam and said sample, saidchannels being further configured to convert said optical signals intorespective electrical signals; a first optical path from said source ofsaid beam to said sample; a second optical path from said sample to saiddetector; and a signal processing module, capable of: receiving saidelectrical signals from said detector; mathematically combiningindividual decay curves in said electrical signals into a decaysupercurve, said supercurve comprising a number of components, eachcomponent having a time constant and a relative contribution to saidsupercurve; extracting time constants from said supercurve; andquantifying the relative contribution of individual components to saidsupercurve.
 2. The apparatus of claim 1, wherein said source of saidbeam of pulsed optical energy is an internally modulated laser.
 3. Theapparatus of claim 1, wherein said signal processing module comprisesone of an FPGA, a DSP chip, an ASIC, a CPU, a microprocessor, amicrocontroller, a single-board computer, a standalone computer, and acloud-based processor.
 4. The apparatus of claim 1, wherein said opticalsignals comprise a fluorescence signal.
 5. The apparatus of claim 1,wherein said sample comprises a suspension of particles; the apparatusfurther comprising: a flow path for said suspension of particles; aflowcell configured as an optical excitation chamber for generating saidoptical signals from interactions between said beam of pulsed opticalenergy and said particles; said flowcell being connected with said flowpath, said first optical path and said second optical path.
 6. Theapparatus of claim 5, wherein the apparatus comprises a flow cytometer.7. The apparatus of claim 6, further comprising: a particle sortingactuator connected with said flow path; an actuator driver connectedwith said actuator, said driver being configured to receive actuationsignals from said signal processing module; and at least one particlecollection receptacle connected with said flow path.
 8. The apparatus ofclaim 7, wherein said particle sorting actuator is based on at least oneflow diversion in said flow path.
 9. The apparatus of claim 8, whereinsaid particle sorting actuator is based on one of a transient bubble, apressurizable chamber, a pressurizable/depressurizable chamber pair, anda pressure transducer.
 10. An apparatus for analyzing an optical signaldecay, comprising: a source of a beam of pulsed optical energy; a sampleholder configured to expose a sample to said beam; a detector, thedetector comprising a number of spectral detection channels, saidchannels being sensitive to distinct wavelength sections of theelectromagnetic spectrum and being configured to detect optical signalsresulting from interactions between said beam and said sample, saidchannels being further configured to convert said optical signals intorespective electrical signals; a first optical path from said source ofsaid beam to said sample; a second optical path from said sample to saiddetector; and a signal processing module, capable of: receiving saidelectrical signals from said detector; mathematically combiningindividual decay curves in said electrical signals into a decaysupercurve, said supercurve comprising a number of components, eachcomponent having a time constant and a relative contribution to saidsupercurve; allocating individual components of said supercurve todiscrete bins of predetermined time constants; and quantifying therelative contribution of individual components to said supercurve. 11.The apparatus of claim 10, wherein said source of said beam of pulsedoptical energy is an internally modulated laser.
 12. The apparatus ofclaim 10, wherein said signal processing module comprises one of anFPGA, a DSP chip, an ASIC, a CPU, a microprocessor, a microcontroller, asingle-board computer, a standalone computer, and a cloud-basedprocessor.
 13. The apparatus of claim 10, wherein said optical signalscomprise a fluorescence signal.
 14. The apparatus of claim 10, whereinsaid sample comprises a suspension of particles; the apparatus furthercomprising: a flow path for said suspension of particles; a flowcellconfigured as an optical excitation chamber for generating said opticalsignals from interactions between said beam of pulsed optical energy andsaid particles; said flowcell being connected with said flow path, saidfirst optical path and said second optical path.
 15. The apparatus ofclaim 14, wherein the apparatus comprises a flow cytometer.
 16. Theapparatus of claim 15, further comprising: a particle sorting actuatorconnected with said flow path; an actuator driver connected with saidactuator, said driver being configured to receive actuation signals fromsaid signal processing module; and at least one particle collectionreceptacle connected with said flow path.
 17. The apparatus of claim 16,wherein said particle sorting actuator is based on at least one flowdiversion in said flow path.
 18. The apparatus of claim 17, wherein saidparticle sorting actuator is based on one of a transient bubble, apressurizable chamber, a pressurizable/depressurizable chamber pair, anda pressure transducer.